Mapping residual malaria transmission in VietnamResearch in context
Summary: Background: Vietnam, as one of the countries in the Greater Mekong Subregion, has committed to eliminating all malaria by 2030. Declining case numbers highlight the country's progress, but challenges including imported cases and pockets of residual transmission remain. To successfully...
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Elsevier
2025-04-01
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| Series: | The Lancet Regional Health. Western Pacific |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666606525000823 |
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| author | Michael A. McPhail Yalemzewod Assefa Gelaw Xuan Thang Nguyen Win Han Oo Freya J.I. Fowkes Duc Thang Ngo Thi Hong Phuc Nguyen Tasmin L. Symons Dan J. Weiss Peter W. Gething |
| author_facet | Michael A. McPhail Yalemzewod Assefa Gelaw Xuan Thang Nguyen Win Han Oo Freya J.I. Fowkes Duc Thang Ngo Thi Hong Phuc Nguyen Tasmin L. Symons Dan J. Weiss Peter W. Gething |
| author_sort | Michael A. McPhail |
| collection | DOAJ |
| description | Summary: Background: Vietnam, as one of the countries in the Greater Mekong Subregion, has committed to eliminating all malaria by 2030. Declining case numbers highlight the country's progress, but challenges including imported cases and pockets of residual transmission remain. To successfully eliminate malaria and to prevent reintroduction of malaria transmission, geostatistical modelling of vulnerability (importation rate) and receptivity (quantified by the reproduction number) of malaria is critical. Methods: Case data from 2019 to 2022 was used to train a range of network and geostatistical models, from which strategically useful metrics were computed. These metrics include vulnerability, which was estimated from the abundance of imported cases, and receptivity, which was estimated based on a transmission model linking cases as well as environmental covariate data. Findings: There is considerable spatiotemporal heterogeneity in the computed metrics. Importations are concentrated in the South Central Coast and Central highlands regions. The importation rate of Plasmodium falciparum is around 2.5 times higher than that of P. vivax. The mean computed reproduction number is less than one, which is consistent with the historical decline in cases and eventual elimination. There are, however, places where the estimated reproduction number can temporarily exceed one, which explains the seasonal case resurgence observed in the case data. The reproduction number is typically higher in forested areas. Interpretation: Receptivity and vulnerability to malaria is spatiotemporally heterogeneous in Vietnam. Despite the average reproduction number being less than one, the spatial pockets and temporal windows of elevated reproduction number could prevent timely elimination of malaria or even lead to a reversal of progress. The predictive maps presented in this paper can inform appropriate intervention strategies to advance goals of malaria elimination. Funding: This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation [INV-055192 and INV-009390/OPP1197730]. The conclusions and opinions expressed in this work are those of the author(s) alone and shall not be attributed to the Foundation. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. Please note works submitted as a preprint have not undergone a peer review process. This work also includes funding support from the Australian Government, National Health and Medical Research Council (Award No: GNT2025280) and Telethon Trust, Western Australia. |
| format | Article |
| id | doaj-art-4f9f4fe210b7400f9ae304b811d3c97e |
| institution | OA Journals |
| issn | 2666-6065 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
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| series | The Lancet Regional Health. Western Pacific |
| spelling | doaj-art-4f9f4fe210b7400f9ae304b811d3c97e2025-08-20T02:09:25ZengElsevierThe Lancet Regional Health. Western Pacific2666-60652025-04-015710154510.1016/j.lanwpc.2025.101545Mapping residual malaria transmission in VietnamResearch in contextMichael A. McPhail0Yalemzewod Assefa Gelaw1Xuan Thang Nguyen2Win Han Oo3Freya J.I. Fowkes4Duc Thang Ngo5Thi Hong Phuc Nguyen6Tasmin L. Symons7Dan J. Weiss8Peter W. Gething9The Kids Research Institute Australia, Perth, WA, Australia; Corresponding author.The Kids Research Institute Australia, Perth, WA, Australia; School of Population Health, Curtin University, Perth, WA, AustraliaNational Institute of Malariology, Parasitology and Entomology, Ministry of Health, Hanoi, VietnamBurnet Institute, 85 Commercial Rd, Melbourne, VIC, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, AustraliaBurnet Institute, 85 Commercial Rd, Melbourne, VIC, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, AustraliaNational Institute of Malariology, Parasitology and Entomology, Ministry of Health, Hanoi, VietnamNational Institute of Malariology, Parasitology and Entomology, Ministry of Health, Hanoi, Vietnam; Hanoi University of Public Health, Hanoi, VietnamThe Kids Research Institute Australia, Perth, WA, Australia; School of Population Health, Curtin University, Perth, WA, AustraliaThe Kids Research Institute Australia, Perth, WA, Australia; School of Population Health, Curtin University, Perth, WA, AustraliaThe Kids Research Institute Australia, Perth, WA, Australia; School of Population Health, Curtin University, Perth, WA, AustraliaSummary: Background: Vietnam, as one of the countries in the Greater Mekong Subregion, has committed to eliminating all malaria by 2030. Declining case numbers highlight the country's progress, but challenges including imported cases and pockets of residual transmission remain. To successfully eliminate malaria and to prevent reintroduction of malaria transmission, geostatistical modelling of vulnerability (importation rate) and receptivity (quantified by the reproduction number) of malaria is critical. Methods: Case data from 2019 to 2022 was used to train a range of network and geostatistical models, from which strategically useful metrics were computed. These metrics include vulnerability, which was estimated from the abundance of imported cases, and receptivity, which was estimated based on a transmission model linking cases as well as environmental covariate data. Findings: There is considerable spatiotemporal heterogeneity in the computed metrics. Importations are concentrated in the South Central Coast and Central highlands regions. The importation rate of Plasmodium falciparum is around 2.5 times higher than that of P. vivax. The mean computed reproduction number is less than one, which is consistent with the historical decline in cases and eventual elimination. There are, however, places where the estimated reproduction number can temporarily exceed one, which explains the seasonal case resurgence observed in the case data. The reproduction number is typically higher in forested areas. Interpretation: Receptivity and vulnerability to malaria is spatiotemporally heterogeneous in Vietnam. Despite the average reproduction number being less than one, the spatial pockets and temporal windows of elevated reproduction number could prevent timely elimination of malaria or even lead to a reversal of progress. The predictive maps presented in this paper can inform appropriate intervention strategies to advance goals of malaria elimination. Funding: This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation [INV-055192 and INV-009390/OPP1197730]. The conclusions and opinions expressed in this work are those of the author(s) alone and shall not be attributed to the Foundation. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. Please note works submitted as a preprint have not undergone a peer review process. This work also includes funding support from the Australian Government, National Health and Medical Research Council (Award No: GNT2025280) and Telethon Trust, Western Australia.http://www.sciencedirect.com/science/article/pii/S2666606525000823MalariaGeospatial modellingReceptivityVulnerabilityRisk map |
| spellingShingle | Michael A. McPhail Yalemzewod Assefa Gelaw Xuan Thang Nguyen Win Han Oo Freya J.I. Fowkes Duc Thang Ngo Thi Hong Phuc Nguyen Tasmin L. Symons Dan J. Weiss Peter W. Gething Mapping residual malaria transmission in VietnamResearch in context The Lancet Regional Health. Western Pacific Malaria Geospatial modelling Receptivity Vulnerability Risk map |
| title | Mapping residual malaria transmission in VietnamResearch in context |
| title_full | Mapping residual malaria transmission in VietnamResearch in context |
| title_fullStr | Mapping residual malaria transmission in VietnamResearch in context |
| title_full_unstemmed | Mapping residual malaria transmission in VietnamResearch in context |
| title_short | Mapping residual malaria transmission in VietnamResearch in context |
| title_sort | mapping residual malaria transmission in vietnamresearch in context |
| topic | Malaria Geospatial modelling Receptivity Vulnerability Risk map |
| url | http://www.sciencedirect.com/science/article/pii/S2666606525000823 |
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